Targeting Incentives to Reduce Habitat Fragmentation
建立理论模型分析如何空间定向激励以恢复森林景观，减少栖息地破碎化，发现边际净收益可能为凸函数，导致最优解为全部或零转化，并通过大规模模拟验证。
Abstract This article develops a theoretical model to analyze the spatial targeting of incentives for the restoration of forested landscapes when wildlife habitat can be enhanced by reducing fragmentation. The key theoretical result is that the marginal net benefits of increasing forest can be convex, in which case corner solutions—converting either none or all of the agricultural land in a section to forest—may be optimal. Corner solutions are directly linked to the spatial process determining habitat benefits and the regulator's incomplete information regarding landowner opportunity costs. We present findings from large‐scale empirical landscape simulations that support our key theoretical results.